Table 1.

Model evaluation

Modelps-R2, %RMSPECP, %
SLA
 CfNA8.1391.2
 Cb16.97.1394.7
 Cn26.06.6695.8
 Lf4.67.9991.3
 Lb23.46.9394.0
 Ln30.76.5395.2
 Sf45.57.5493.6
 Sb58.56.3197.7
 Sn60.26.1397.7
Nm
 CfNA7.1693.3
 Cb12.56.9593.2
 Cn19.46.4792.7
 Lf5.27.2893.2
 Lb16.76.7194.3
 Ln24.16.4294.6
 Sf44.27.1993.6
 Sb53.76.3696.1
 Sn54.86.1896.1
Pm
 CfNA0.8690.5
 Cb5.30.8690.5
 Cn28.10.7891.1
 Lf25.60.8487.2
 Lb32.80.8585.3
 Ln35.40.8287.0
 Sf62.00.8390.7
 Sb66.70.8192.0
 Sn67.60.8091.3
  • Shown are the pseudo-R2 (ps-R2), RMSPE, and CP statistics for all nine models, for each of the three traits. The entries in boldface type correspond to the model producing highest ps-R2, lowest RMSPE, or CP closest to 0.95. The categorical PFT-free model (Cf) produces a constant estimate and hence ps-R2 is not defined. Each model is indicated by a two-letter abbreviation: C, categorical (no regression); L, linear (linear regression); and S, spatial (linear regression with spatial term) and the accompanying PFT resolution: f, PFT-free (no PFT information); b, broad (4-PFT); and n, narrow (14-PFT).